Data Architect

World Vision

21d•Remote

About The Position

The Data Architect is responsible for the design, governance, and integrity of World Vision Canada's data architecture. The role defines how data is structured, stored, integrated, and made available for reporting, analytics, and artificial intelligence, translating business information requirements into a governed and reusable data foundation. It ensures data is consistent across systems, reliable for decision-making, and able to support the organization as its technology environment changes. Reporting to the Director, Data Intelligence, the Data Architect develops the organization's data architecture framework and principles for approval and is accountable for their application across the enterprise. The role owns data architecture for the multi-year transformation program and sets the multi-year direction and roadmap for the data architecture and platform. It is hands-on, with results achieved through modernizing data flows, publishing standards, documentation, and design reviews. Day-to-day operational support is ad hoc and provided as available.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent professional experience.
Ten or more years working in data management disciplines such as data modelling, data engineering, or data science.
Five or more years in data architecture, including design of lakehouse or warehouse-native patterns and batch and streaming data flows in Snowflake and other cloud data platforms.
Demonstrated accountability for an enterprise data architecture, including setting standards adopted across delivery teams and vendors and presenting architecture direction to senior leadership for approval.
Demonstrated delivery of master-data and golden-record solutions, governed reusable data products, and warehouse-native customer data platforms.
Demonstrated experience setting data design direction for solution architects and delivery partners within an established technology or architecture function.
Experience designing data protection, classification, and access controls for sensitive data.
Ability to define data and application-programming-interface contracts in advance of build, including use of schema registries and contract testing.
Advanced data modelling across conceptual, logical, and physical layers, including relational and dimensional modelling, and strong SQL.
Familiarity with modern transformation frameworks such as dbt, ELT patterns, and orchestration tooling sufficient to define standards and review implementations.
Familiarity with Python or similar scripting languages for prototyping and automation.
Understanding of continuous integration and delivery and automated testing practices for data, including contract and schema testing, sufficient to embed them in standards and review vendor delivery.
Command of modern data architecture paradigms, including data mesh, data fabric, and lakehouse, sufficient to choose between them and defend the choice.
Familiarity with data catalog and metadata management tooling.
Proficiency with architecture modelling notations and tools for producing models and diagrams, such as ArchiMate or UML.
Experience working in environments using Enterprise Agile frameworks.
Clear communication with technical specialists and non-technical stakeholders; ability to build agreement on design direction across technical and business teams.
Sound judgement in complex and ambiguous design problems, balancing long-term architectural integrity with near-term delivery needs.
Ability to record design decisions, apply standards consistently, and support recommendations with evidence.

Nice To Haves

Enterprise-architecture or cloud data-platform certification, such as TOGAF or a recognized cloud data credential.
Experience in a nonprofit or mission-driven organization.

Responsibilities

Design the enterprise data architecture, including conceptual, logical, and physical architecture, the data platform, canonical data models, and standards governing data structure, storage, and movement.
Develop and present the data architecture, roadmap, and material design decisions to senior leadership for approval; frame options and trade-offs and set multi-year direction for the data architecture and platform.
Define contract-first data integration and interoperability patterns, interfaces, schema and interface contracts, and reusable standards for systems exchanging data, including secure data-sharing with federated partner organizations.
Set data architecture requirements for solution designs, resolve data design questions arising within solution architecture, and ensure individual solutions remain coherent with the wider data architecture.
Design governed, reusable data products and master data structures, including consolidated master records and analytical models, for reporting, analytics, and machine learning; ensure they are documented, discoverable, and reusable.
Establish data quality, master data management, retention, and remediation controls and standards; monitor adherence, direct remediation of data quality and definition issues at source, and withhold acceptance when controls are not met.
Set data quality and design requirements for reliable analytics and AI data, including completeness, consistency, labelling, and documented meaning.
Define standards for how analytical and machine-learning workloads consume governed data, and design for platform portability to avoid undue dependence on a single vendor or platform.
Establish standards for data classification, protection, and access, particularly for sensitive information and data concerning donors, employees, and vulnerable populations, including children; incorporate privacy and access controls from the outset and meet or exceed regulatory and organizational obligations.
Produce and maintain architecture documentation, including conceptual, logical, and physical data models; current and target state reference architectures; data flow and integration diagrams; architecture decision records; and standards documentation.
Review solution and vendor designs against data architecture standards, prepare and review architecture decision records, and confirm alignment before designs proceed.
Guide delivery teams through implementation, ensure delivered systems conform to the architecture, and adjust the architecture when implementation demonstrates that changes are needed.